Jacek Radzikowski

#Earthquake: Twitter as a Distributed Sensor System

Social media feeds are rapidly emerging as a novel avenue for the contribution and dissemination of information that is often geographic. Their content often includes references to events occurring at, or affecting specific locations. Within this article we analyze the spatial and temporal characteristics of the twitter feed activity responding to a 5.8 magnitude earthquake which occurred on the East Coast of the United States (US) on August 23, 2011. We argue that these feeds represent a hybrid form of a sensor system that allows for the identification and localization of the impact area of the event. By contrasting this with comparable content collected through the dedicated crowdsourcing ‘Did You Feel It?’ (DYFI) website of the U.S. Geological Survey we assess the potential of the use of harvested social media content for event monitoring. The experiments support the notion that people act as sensors to give us comparable results in a timely manner, and can complement other sources of data to enhance our situational awareness and improve our understanding and response to such events.

Geosocial gauge: a system prototype for knowledge discovery from social media

The remarkable success of online social media sites marks a shift in the way people connect and share information. Much of this information now contains some form of geographical content because of the proliferation of location-aware devices, thus fostering the emergence of geosocial media – a new type of user-generated geospatial information. Through geosocial media we are able, for the first time, to observe human activities in scales and resolutions that were so far unavailable. Furthermore, the wide spectrum of social media data and service types provides a multitude of perspectives on real-world activities and happenings, thus opening new frontiers in geosocial knowledge discovery. However, gleaning knowledge from geosocial media is a challenging task, as they tend to be unstructured and thematically diverse. To address these challenges, this article presents a system prototype for harvesting, processing, modeling, and integrating heterogeneous social media feeds towards the generation of geosocial knowledge. Our article addresses primarily two key components of this system prototype: a novel data model for heterogeneous social media feeds and a corresponding general system architecture. We present these key components and demonstrate their implementation in our system prototype, GeoSocial Gauge.

The Measles Vaccination Narrative in Twitter: A Quantitative Analysis

Background The emergence of social media is providing an alternative avenue for information exchange and opinion formation on health-related issues. Collective discourse in such media leads to the formation of a complex narrative, conveying public views and perceptions. Objective This paper presents a study of Twitter narrative regarding vaccination in the aftermath of the 2015 measles outbreak, both in terms of its cyber and physical characteristics. We aimed to contribute to the analysis of the data, as well as presenting a quantitative interdisciplinary approach to analyze such open-source data in the context of health narratives. Methods We collected 669,136 tweets referring to vaccination from February 1 to March 9, 2015. These tweets were analyzed to identify key terms, connections among such terms, retweet patterns, the structure of the narrative, and connections to the geographical space. Results The data analysis captures the anatomy of the themes and relations that make up the discussion about vaccination in Twitter. The results highlight the higher impact of stories contributed by news organizations compared to direct tweets by health organizations in communicating health-related information. They also capture the structure of the antivaccination narrative and its terms of reference. Analysis also revealed the relationship between community engagement in Twitter and state policies regarding child vaccination. Residents of Vermont and Oregon, the two states with the highest rates of non-medical exemption from school-entry vaccines nationwide, are leading the social media discussion in terms of participation. Conclusions The interdisciplinary study of health-related debates in social media across the cyber-physical debate nexus leads to a greater understanding of public concerns, views, and responses to health-related issues. Further coalescing such capabilities shows promise towards advancing health communication, thus supporting the design of more effective strategies that take into account the complex and evolving public views of health issues.

Demarcating new boundaries: mapping virtual polycentric communities through social media content

The proliferation of social media has led to the emergence of a new type of geospatial information that defies the conventions of authoritative or volunteered geographic information, yet can be harvested to reveal unique and dynamic information about people and their activities. In this paper we address the identification and mapping of global virtual communities formed around issues of specific national interest. We refer to these connected virtual communities formed around issues related to a specific state as the polycentric virtual equivalent of that state. Identifying, mapping, and analyzing these virtual communities is a novel challenge for our community, and this is the subject we pursue in this paper. We present these communities relative to established conventions of statehood, address the harvesting of relevant geographical information from social media feeds, and discuss the challenge of visualizing such information. In order to do so we use the current geopolitical situation in Syria as a demonstrative example.

A performance study of job management systems

Job Management Systems (JMSs) efficiently schedule and monitor jobs in parallel and distributed computing environments. Therefore, they are critical for improving the utilization of expensive resources in high‐performance computing systems and centers, and an important component of Grid software infrastructure. With many JMSs available commercially and in the public domain, it is difficult to choose an optimum JMS for a given computing environment. In this paper, we present the results of the first empirical study of JMSs reported in the literature. Four commonly used systems, LSF, PBS Pro, Sun Grid Engine/CODINE, and Condor were considered. The study has revealed important strengths and weaknesses of these JMSs under different operational conditions. For example, LSF was shown to exhibit excellent throughput for a wide range of job types and submission rates. Alternatively, CODINE appeared to outperform other systems in terms of the average turn‐around time for small jobs, and PBS appeared to excel in terms of turn‐around time for relatively larger jobs. Copyright

Linking cyber and physical spaces through community detection and clustering in social media feeds

Abstract Over the last decade we have witnessed a significant growth in the use of social media. Interactions within their context lead to the establishment of groups that function at the intersection of the physical and cyber spaces, and as such represent hybrid communities. Gaining a better understanding of how information flows in these hybrid communities is a substantial scientific challenge with significant implications on our ability to better harness crowd-contributed content. This paper addresses this challenge by studying how information propagates and evolves over time at the intersection of the physical and cyber spaces. By analyzing the spatial footprint, social network structure, and content in both physical and cyber spaces we advance our understanding of the information propagation mechanisms in social media. The utility of this approach is demonstrated in two real-world case studies, the first reflecting a planned event (the Occupy Wall Street – OWS – movement’s Day of Action in November 2011), and the second reflecting an unexpected disaster (the Boston Marathon bombing in April 2013). Our findings highlight the intricate nature of the propagation and evolution of information both within and across cyber and physical spaces, as well as the role of hybrid networks in the exchange of information between these spaces.

Performance evaluation of selected job management systems

One important component of grid software infrastructure and parallel systems management is the Job Management System (JMS). With many JMSs available commercially and in public domain, it is difficult to choose the most efficient JMS for a given computing environment. All previous comparisons of JMSs had only a conceptual character. In this paper, we present the results of the first empirical study of JMSs reported in the literature. Two most popular commercial systems, LSF and PBS Pro, were included in our study. The study has revealed important strengths and weaknesses of these JMSs under different operational conditions. For example, LSF was shown to exhibit excellent throughput for a wide range of job types and submission rates. On the other hand, PBS appeared to excel in terms of turn-around time. Whenever possible, our study have tried to identify and explain the reasons behind the observed behavior of investigated JMSs.

Towards a collaborative geosocial analysis workbench

Social media contributions are manifestations of humans acting as sensors, participating in activities, reacting to events, and reporting issues that are considered important. Harvesting this information offers a unique opportunity to monitor the human landscape, and gain unparalleled situational awareness, especially as it relates to sociocultural dynamics. However, this requires the emergence of a novel GeoSocial analysis paradigm. Towards this goal, in this paper we present a framework for collaborative GeoSocial analysis, which is designed around data harvesting from social media feeds (starting with twitter and flickr) and the concept of a collaborative GeoSocial Analysis Workbench (G-SAW). We present key concepts of this framework, and early test implementation results in order to demonstrate the potential of the G-SAW framework for enhanced situational awareness.

Effective utilization and reconfiguration of distributed hardware resources using job management systems

Reconfigurable hardware resources are very expensive, and yet can be underutilized. This paper describes a middleware capable of discovering underutilized computing nodes with FPGA-based accelerator boards in a networked environment. Using an extended job management system (JMS), this middleware permits sharing reconfigurable resources at least among the members of the same organization. Traditional resources, such as CPU time of loosely coupled workstations can be shared using a variety of existing job management systems (JMS). We analyzed four of these systems, LSF, Sun Grid Engine/CODINE, PBS Pro, and Condor from the point of view of their functional characteristics and ease of extension to support reconfigurable hardware. LSF was shown to efficiently address the majority of identified requirements. The general architecture of the extended system was developed, and the exact techniques of extending LSF, CODINE, and PBS Pro to manage FPGA-based accelerator boards were identified. The system architecture was verified experimentally for the specific case of LSF and three types of FPGA accelerator boards. The utilization of FPGA boards was demonstrated to reach up to 86% in our experimental setting consisting of Linux and Windows NT workstations.

International Relations: State-Driven and Citizen-Driven Networks

The international community can be viewed as a set of networks manifested through various transnational activities. The availability of longitudinal data sets such as international arms trades and United Nations General Assembly (UNGA) allows for the study of state-driven interactions over time. In parallel to this top-down approach, the recent emergence of social media is fostering a bottom-up and citizen-driven avenue for international relations (IRs). The comparison of these two network types offers a new lens to study the alignment between states and their people. This article presents a network-driven approach to analyze communities as they are established through different forms of bottom-up (e.g., Twitter) and top-down (e.g., UNGA voting records and international arms trade records) IRs. By constructing and comparing different network communities, we were able to evaluate the similarities between state-driven and citizen-driven networks. In order to validate our approach we identified communities in UNGA voting records during and after the Cold War. Our approach showed that the similarity between UNGA communities during and after the Cold War was 0.55 and 0.81, respectively (in a 0–1 scale). To explore the state- versus citizen-driven interactions, we focused on the recent events in Syria within Twitter over a sample period of 1 month. The analysis of these data show a clear misalignment (0.25) between citizen-formed international networks and the ones established by the Syrian government (e.g., through its UNGA voting patterns).